Abstract: This application relates to compounds of Formula I: or pharmaceutically acceptable salts thereof, which are inhibitors of TAM kinases which are useful for the treatment of disorders such as cancer.

Abstract: Embodiments for generating a reservoir performance forecast are provided. The embodiments may be executed by a computer system. In one embodiment, a method includes obtaining inflow performance relationship data generated from a physics-based subsurface-surface coupled simulation model having a surface, a subsurface, and one or more wells fluidly connecting the subsurface to the surface. The inflow performance relationship data comprises performance data for at least one phase of fluid for each well. The method also includes generating a performance forecast for the reservoir using a subsurface simulator and a surface simulator. The subsurface simulator uses the inflow performance relationship data to represent the subsurface during generation of the performance forecast, and the performance forecast satisfies constraints solved by the surface simulator. In one embodiment, a method does not utilize a surface simulator.

Abstract: Embodiments of generating a field development plan for a hydrocarbon field development are provided herein. One embodiment comprises generating a plurality of training reservoir models of varying values of input channels of a reservoir template; normalizing the varying values of the input channels to generate normalized values of the input channels; constructing a policy neural network and a value neural network that project a state represented by the normalized values of the input channels to a field development action and a value of the state respectively; and training the policy neural network and the value neural network using deep reinforcement learning on the plurality of training reservoir models with a reservoir simulator as an environment such that the policy neural network generates a field development plan. A field development plan may be generated for a target reservoir on the reservoir template using the trained policy network and the reservoir simulator.

Abstract: A method, system and computer program product is disclosed for utilizing proxy models to evaluate a subterranean reservoir. The method includes constructing a proxy model from a set of sampling points to approximate simulation outputs of a reservoir model. The set of sampling points is updated by adding at least one new sampling point that is selected from a location associated with surface non-linearities such as gradients, curvature, and bending energy. Response surface values at new sampling points and distances to existing sampling points can also be used to evaluate new sampling points. Proxy models are refined with the updated set of sampling points until the proxy model satisfies a predetermined stopping criterion, such as when a predetermined number of iterations are reached or when changes to the response surface are below a predetermined threshold.

Abstract: A method, system and computer program product is disclosed for utilizing proxy models to evaluate a subterranean reservoir. The method includes constructing a proxy model from a set of sampling points to approximate simulation outputs of a reservoir model. The set of sampling points is updated by adding at least one new sampling point that is selected from a location associated with surface non-linearities such as gradients, curvature, and bending energy. Response surface values at new sampling points and distances to existing sampling points can also be used to evaluate new sampling points. Proxy models are refined with the updated set of sampling points until the proxy model satisfies a predetermined stopping criterion, such as when a predetermined number of iterations are reached or when changes to the response surface are below a predetermined threshold.